{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cdb78989-501a-419d-9d5c-032652e37fda",
   "metadata": {},
   "source": [
    "# Simple Time-Series Line Plot\n",
    "\n",
    "A basic time-series line plot showing values across dates. This example demonstrates how to visualize trends over time using datetime indexes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "543cdb28-f080-4977-b7fe-626cd310f468",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import hvplot.pandas  # noqa\n",
    "\n",
    "np.random.seed(0)\n",
    "dates = pd.date_range(\"2024-01-01\", periods=30, freq=\"D\")\n",
    "values = np.cumsum(np.random.randn(30))\n",
    "df = pd.DataFrame({'date': dates, 'value': values}).set_index('date')\n",
    "\n",
    "df.hvplot.line(title=\"Simple Time-Series Line Plot (Bokeh)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "091895ee-49b8-45a2-ac26-f9610e38305f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import hvplot.pandas  # noqa\n",
    "hvplot.extension('matplotlib')\n",
    "\n",
    "np.random.seed(0)\n",
    "dates = pd.date_range(\"2024-01-01\", periods=30, freq=\"D\")\n",
    "values = np.cumsum(np.random.randn(30))\n",
    "df = pd.DataFrame({'date': dates, 'value': values}).set_index('date')\n",
    "\n",
    "df.hvplot.line(title=\"Simple Time-Series Line Plot (Matplotlib)\", rot=45)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d40ff39-3107-454b-a9a6-5d7d06738118",
   "metadata": {},
   "source": [
    ":::{seealso}\n",
    "- [Line Plots reference documentation](../../ref/api/manual/hvplot.hvPlot.line.ipynb).\n",
    ":::"
   ]
  }
 ],
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